“Not all smart people work for you.”
~ Bill Joy, the co-founder of Sun Microsystems

With an increased focus on innovation, every R&D manager wants to figure out a way to maximize research and development productivity. Right R&D collaboration is a way as it helps identify new ideas and in their faster implementation.

From knowledge-based views, collaboration leads to pooling of complementary competencies that fills the knowledge gaps of collaborators. Further, it increases the chances of association between different ideas which creates a chain of connected ideas that result in something innovative.

There is no dearth of empirical studies supporting the point. Brouwer and Kleinknecht, for instance, found that companies that enter into R&D collaboration file more patent than non-collaborators.  Similarly, Van Ophem et al in their paper reveal that firms collaborating file more patents than firms focusing on internal R&D.

Though patent filing isn’t indicative of a final product or commercial success of a new product it is an indication of inventive activities. Also, there is a positive relationship between a R&D collaboration and successful termination of a project and introduction of a new product in the market.

Apart from the knowledge-based angle, if we look at R&D collaboration from resource-based view, external knowledge plays a crucial role in exploiting resources and developing a long-term competitive advantage. Ford, for example, in order to develop a fully autonomous vehicle for ride-sharing by 2021 is collaborating for four startups Velodyne, Civil Maps, Nirenberg Neuroscience LLC, and SAIPS. Not only has these four, Ford, to achieve the same target, invested $1Bn in a joint venture with ARGO AI.

Now the question is how R&D collaboration drives innovative success and the even bigger question is how to go about it. Both of which we have answered in the subsequent sections of this article. Please keep reading:

What type of R&D Collaboration Can Lead to Innovative Success?

Before you go searching for an R&D partner, there are few things which you must know as it can affect the outcome of R&D collaboration. How? Because if an organization or a team fail to absorb and use the knowledge gained from an R&D alliance, it makes the chances of a successful collaboration thin.

We can divide R&D partnerships, like research, into two types: exploitative and explorative. These two types further have two same branches – internal and external. Have a look:

Exploitative research or R&D collaboration is a type where firms focus on using existing knowledge of each other to achieve a goal. While in the type Explorative, firms collaborate to gain new knowledge and uncover new opportunities.

Internal exploitation as the name suggests is when firm exploits already acquired knowledge of different dept. to achieve a common goal. We can call it an internal collaboration of various functional teams.

A recent study identifies CPG (Consumer Packaged Goods) professionals ranking collaboration among the top three factors for innovation success. Despite this, 74% of CPG professionals believe that their company is not collaborating effectively. How internal collaboration drives innovation success, is covered in this benchmark study by Neilson.

Similarly, Internal Exploration is when different teams collaborate for exploring new horizon. In external exploration alliances, firms are motivated to discover something new and to push boundaries of basic science. In external exploitation, firms seek to leverage their existing capabilities.

There are multiple empirical studies highlighting that an understanding of what kind of R&D collaboration firms are entering into, gives a more fine-grained understanding of outcomes.  Also, there exist multiple combinations of exploration and exploitation alliances. Further, it’s vital to find a combination beneficial to performance as only certain combinations bring fruitful results while a lot do more harm than good.

Frank Rothaermel in Incumbent’s advantage through exploiting complementary assets via interfirm cooperation, for example, notes the higher performance of Pharma Company that focuses on external exploitation than external exploration when it shifts to biotechnology.  Rothaermel, in another study, with his colleague Deeds finds that biotech startups that leverage exploration and exploitation alliances in sequence achieve superior product development performances.

Frank Rothaermel and Ha Hoang conclude the paper Leveraging internal and external experience: exploration, exploitation, and R&D project performance with the followings:

In particular, we find that a combination of internal exploration with external exploitation improved R&D project performance, while a combination of internal exploitation and external exploration reduced R&D project performance. It appears that internal exploration competencies lay the necessary foundation to leverage external experience.

Thus, we can say that for a R&D partnership to bring desired results, your firm has to have a clear understanding of what kind of combination it will go ahead with. Also, before going for external collaboration, you have to fine-tune the internal collaboration. This is aptly put by Swami Vivekananda:

“Conquer yourself and the whole universe is yours.”
~ Swami Vivekananda

Let’s move ahead and find how you can find R&D partners for collaboration using a data-backed approach.

How to find the right R&D partner?

Locate companies and universities solving the problem you are trying to solve and not just those working in your area. A broad depiction of the area of operation of companies and universities isn’t going to help.

In energy storage domain, for example, you cannot pick companies that are battery manufacturers. Why? Because a different manufacturer will be working on a different type of battery – Lithium, Nickel, Lithium-Air, Lithium Sulphur, etc.

Even in a specific technology area, these entities would be solving a variety of different problems ranging from heating, swelling, life cycle, charging/discharging to dendrite formation, energy density and many other. Thus, selecting a company/university solving the same problem becomes a first crucial step to get a qualified list of potential collaborators.

Next is an assessment of capability. I guess you already have seen what is coming next. This step involves checking existing work of possible collaborator to benchmark what solutions have been developed and what benchmarks have been achieved by them in solving a particular problem.

After this come comparatively easy task of checking collaboration history of a can-be-a-collaborator. In the next step, you can classify these collaborators into established entities and new entrants and then on the basis of your preference, you can select a company/university to collaborate with.

Many companies prefer going with an established player with enough knowledge of a particular area. Many focus on a new entrant that can add new knowledge. There are financial criteria to consider and few more, however, my chief focus in on the technical pillar of decision making.

Do you feel this to be a lot of work and something which is time intensive? I think this is because you have not used North Star yet. Would like to know how North Star can help you save time invested in information collection? Great Click here to request a demo.